@Article{jai.2025.061437,
AUTHOR = {Guodong Yuan, Jin Xie},
TITLE = {Continuous Monitoring of Multi-Robot Based on Target Point Uncertainty},
JOURNAL = {Journal on Artificial Intelligence},
VOLUME = {7},
YEAR = {2025},
NUMBER = {1},
PAGES = {1--16},
URL = {http://www.techscience.com/jai/v7n1/59997},
ISSN = {2579-003X},
ABSTRACT = {This paper addresses the problem of access efficiency in multi-robot systems to the monitoring area. A distributed algorithm for multi-robot continuous monitoring, based on the uncertainty of target points, is used to minimize the uncertainty and instantaneous idle time of all target points in the task domain, while maintaining a certain access frequency to the entire task domain at regular time intervals. During monitoring, the robot uses shared information to evaluate the cumulative uncertainty and idle time of the target points, and combines the update list collected from adjacent target points with a utility function to determine the target points to be visited online. At the same time, the paper further delves into the impact of stability and scalability on multi-robot continuous monitoring algorithms in different surveillance environments. Finally, through simulation experiments and physical experiments in different environments, it has been demonstrated that the use of the algorithm presented in the paper leads to superior overall monitoring performance for robotic systems, providing assistance for research on large-scale robotic systems.},
DOI = {10.32604/jai.2025.061437}
}